Intermediate Data Platform Engineer

Data Platform Engineer – Intermediate Key Highlights ️ Build and expand core data platform components powering analytics, experimentation, and algorithm development ⚡ Develop scalable ETL, streaming, and metadata systems using Spark, Kafka, and modern lakehouse technologies Support high-volume data transformation, federated querying, and performance optimization Strengthen RBAC, data governance, and secure access patterns for multi-team data environments Enable experimentation and data development with reliable tooling and automated data workflows Position Overview We are seeking an Intermediate Data Platform Engineer to help build and scale a modern data ecosystem. In this role, you’ll contribute to distributed data systems, ETL/streaming pipelines, metadata platforms, and frameworks that support experimentation across the organization. You will develop platform features, enhance observability, ensure data reliability, and collaborate with engineering and data science teams to support new initiatives. Key Responsibilities Data Platform Engineering Build and maintain scalable data storage, transformation, and processing systems Support Iceberg-based data lakehouse architecture and metadata catalogs Develop ETL and streaming pipelines using Spark, Kafka, Parquet, and Iceberg Build backend services in Python, Go, Scala, or Java to enhance platform capabilities Contribute to Trino query performance and metadata optimization Experimentation & Analytics Enablement Develop tooling that improves experiment design, tracking, and analysis Collaborate with data science and analytics teams to support experimentation workflows Automate components of A/B testing and experimentation frameworks Data Reliability, Security & Governance Maintain and improve platform-level RBAC and AWS IAM configuration Use Datadog for logging, alerting, and monitoring platform performance Support schema evolution, data quality, and reproducibility across pipelines Infrastructure & Deployment Deploy and support services using Kubernetes and Helm Improve automation, performance, and cost efficiency of data workloads Contribute to capacity planning for data-intensive services Collaboration & Documentation Participate in cross-team engineering discussions Document platform components to support internal stakeholders Qualifications Degree in Computer Science, Engineering, or related field 3+ years in data platform, data engineering, or platform engineering Production-level coding experience in Python , Go , Scala , or Java Experience supporting Iceberg-based data warehouses Hands-on experience with Spark , Kafka , Trino , and distributed systems Familiarity with RBAC systems, IAM, and data governance principles Experience with Kubernetes, Helm, and CI/CD workflows Strong troubleshooting and communication skills Why Join Us Join a team focused on building scalable, modern data infrastructure that powers experimentation and analytics. You’ll gain exposure to leading-edge tools and architectures while contributing to systems used across the organization.